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The objective of the present study is to systematically quantify the along-track resolution of Satellite for Argos and AltiKa (SARAL)/AltiKa and Environmental Satellite (ENVISAT)-RA2 altimeters over continental margins. Spectral coherence and power spectral density estimated from pairs of stacked (averaged) sea surface height (SSH) profiles from repeat tracks as a function of wave number are used to estimate along-track resolution and noise characteristics, respectively. The analyses were carried out along 96 SARAL/AltiKa and ENIVISAT-RA2 tracks covering continental margins of India, Gulf of Mexico, and South America. Our study clearly suggests that for all three sites the short-wavelength resolution of SARAL/AltiKa (15–18 km) is ~27–33% better than ENVISAT-RA2 (22–25 km) data. Variations in sediment thickness along the continental margins have significant influence in the along-track resolution of both altimeters. Strong geoid signals owing to thin sediments (0.1–0.3 km thick) along the South American margin provided higher resolution for both SARAL/AltiKa (15 km) and ENVISAT-RA2 (22 km) altimeters. Conversely, over the continental margins of India and Gulf of Mexico with huge sediment thickness (1–20 km), the resolution of SARAL/AltiKa and ENVISAT-RA2 drops to 18 and 25 km, respectively. We also observe that resolution of both altimeters is higher by 1–2 km for continental margins with narrow shelf. The present study has implications in the generation of high-resolution marine geoid and gravity anomalies using SARAL/AltiKa along with other altimeters. [ABSTRACT FROM AUTHOR]

Despite the tremendous attention given to conservation projects in the Neotropics, few published studies have documented remote sensing studies in tropical highland areas. Even fewer publications have addressed the use of topographic normalization methods in these regions. This article discusses the influence of anisotropic reflectance patterns on land cover classification for two study areas characterized by very rugged terrain and high relief. Landsat Thematic Mapper subscenes for sites in both Costa Rica and Ecuador were corrected using both Lambertian and non-Lambertian models. While use of the Lambertian model proved inappropriate for these mountainous areas, application of the non-Lambertian model enhanced classification accuracies. [ABSTRACT FROM AUTHOR]

Different approaches to the classification of remotely sensed data of mangroves are reviewed, and five different methodologies identified. Landsat TM, SPOT XS and CASI data of mangroves from the Turks and Caicos Islands, were classified using each method. All classifications of SPOT XS data failed to discriminate satisfactorily between mangrove and non-mangrove vegetation. Classification accuracy of CASI data was higher than Landsat TM for all methods, and more mangrove classes could be discriminated. Merging Landsat TM and SPOT XP data improved visual interpretation of images, but did not enhance discrimination of different mangrove categories. The most accurate combination of sensor and image processing method for mapping the mangroves of the eastern Caribbean islands is identified. [ABSTRACT FROM AUTHOR]